The application of controlled natural language on carbon market domain knowledge for enhanced retrieval of information

Abstract

Natural language processing has been used in modelling knowledge about different domains for use in different applications, particularly to those with minimal computer science skills. Although natural language is easy to learn, it is often riddled with ambiguities, vagueness and a very high potential for inconsistencies. Thus, controlled natural language, a subset of natural language has emerged and promises to improve on some major natural language deficiencies. Given the multiplicity of controlled natural languages, Attempto Controlled English (ACE), one of the leading controlled natural languages, was chosen and explored to represent knowledge about the domain of carbon market. The outcome of this study is a prototypical controlled natural language carbon market ontology that can be used in making informed decisions about investment in carbon marketing. In order to establish the suitability and purpose for which the prototype was developed, it was evaluated using appropriate techniques and ontology reasoners.